Most documents are structured to organize their contents. For example, a document may be structured to organize its contents into various regions, such as a table of contents, a body, an index, etc. The structure of some documents may be hierarchical, such that document regions are further divisible into sub-regions. For example, a document body may be divided into chapters, paragraphs, etc. Document structure may depend on document type and/or document contents.
With the proliferation of computers and electronic communication, documents are now commonly represented electronically. A typical electronic representation of a document includes data reflective of the documents contents. In some cases, an electronic representation of a document may include data reflective of the document's structure. Inclusion of data reflective of the document's structure facilitates automatic processing of that document. For example, a document's title may be automatically modified using structural data that identifies the title amongst the document's contents. Similarly, titles of two different documents may be automatically compared using structural data for those documents.
In recent years, one type of document that has become more commonly represented electronically is the patient order set. A patient order set is a form fillable by a doctor to prescribe a course of treatment for a hospital patient. A typical patient order form includes a multitude of treatment options, from which a doctor may select. Patient order sets are often structured to organize treatment options by treatment type, drug type, symptom type, patient type, etc. However, electronic representations of patient order sets typically do not include data reflective of such structure. Moreover, many organizations create their patient order sets using off-the-shelf word processing software which do not have the capability to process data reflective of such structure. As such, automatic processing of patient order sets, e.g., to modify or compare their contents, has been difficult.